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Spinner, N. B.

Publications and source records attributed to Spinner, N. B..

2 recordsLinked to original sources

Exome Sequencing in Individuals with Isolated Biliary Atresia

Biliary atresia (BA) is a severe pediatric liver disease resulting in necroinflammatory obliteration of the extrahepatic biliary tree. BA presents within the first few months of life as either an isolated finding or with additional syndromic features. The etiology of isolated BA is unknown, with evidence for infectious, environmental, and genetic risk factors described. However, to date, there are no definitive causal genes identified for isolated BA in humans, and the question of whether single gene defects play a major role remains open. We performed exome-sequencing in 100 North American patients of European descent with isolated BA (including 30 parent-child trios) and considered several experimental designs to identify potentially deleterious protein-altering variants that may be involved in the disease. In a case-only analysis, we did not identify genes with variants shared among more than two probands, and burden tests of rare variants using a case-case control design did not yield significant results. In the trio analysis of 30 simplex families (patient and parent trios), we identified 66 de novo variants in 66 genes including a nonsense variant, p.(Cys30Ter), in the gene STIP1. STIP1 is a co-chaperone for the heat-shock protein, HSP90AA1, and has been shown to have diverse functions in yeast, flies and mammals, including stress-response. ConclusionOur results do not support the hypothesis that a simple genetic model is responsible for the majority of cases of isolated BA. Our finding of a de novo mutation in a candidate gene for BA (STIP1) linked to evolutionarily conserved stress responses suggests further exploration of how genetic susceptibility and environmental exposure interact to cause BA is warranted.

genetics↗

Rapid interpretation of clinical exomes using Phenoxome: a computational phenotype-driven approach

Clinical exome sequencing (CES) has become the preferred diagnostic platform for complex pediatric disorders with suspected monogenic etiologies, solving up to 20%-50% of cases depending on indication. Despite rapid advancements in CES analysis, the major challenge still resides in identifying the casual variants among the thousands of variants detected during CES testing, and thus establishing a molecular diagnosis. To improve the clinical exome diagnostic efficiency, we developed Phenoxome, a robust phenotype-driven model that adopts a network-based approach to facilitate automated variant prioritization and subsequent classification. Phenoxome dissects the phenotypic manifestation of a patient in conjunction with their genomic profile to filter and then prioritize putative pathogenic variants. To validate our method, we have compiled a clinical cohort of 105 positive patient samples (i.e. at least one reported pathogenic variant) that represent a wide range of genetic heterogeneity from The Childrens Hospital of Philadelphia. Our approach identifies the causative variants within the top 5, 10, or 25 candidates in more than 50%, 71%, or 88% of these patient samples respectively. Furthermore, we show that our method is optimized for clinical testing by yielding superior ranking of the pathogenic variants compared to current state-of-art methods. The web application of Phenoxome is available to the public at http://phenoxome.chop.edu/.

bioinformatics↗